text: import os
  
  #initializing path
  
  DATASET_PATH = "Cyclone_Wildfire_Flood_Earthquake_Database"
  
  # class labels
  
  CLASSES = ["Cyclone", "Earthquake", "Flood", "Wildfire"]
  
  #sizing the training
  
  TRAIN_SPLIT = 0.75
  VAL_SPLIT = 0.1
  TEST_SPLIT = 0.25
  
  # min_lr,max_lr,batch_size,step_size,cyclic_learning_rate,number of epoches
  
  MIN_LR = 1e-6
  MAX_LR = 1e-4
  BATCH_SIZE = 32
  STEP_SIZE =8
  CLR_METHOD = "traingular"
  NUM_EPOCHES = 48
  
  #seriaized model after training
  MODEL_PATH = os.path.sep.join(["output", "natural_disaster.model"])
  
  LRFIND_PLOT_PATH = os.path.sep.join(["output","lrfind_plot.png"])
  TRAINING_PLOT_PATH = os.path.sep.join(["output","training_plot.png"])
  CLR_PLOT_PATH = os.path.sep.join(["output", "clr_plot.png"])
  